This course will provide you with professional knowledge on the application of the ISO DIN EN 9001 standard, as well as on the planning, implementation, maintenance, and effectiveness monitoring of a quality management system. You will also learn how to use statistical software to analyze data.
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Certificates: Certificate "Quality representative with TÜV Rheinland-certified qualification"
Certificate "Statistics and data analysis" -
Examination: Praxisbezogene Projektarbeiten mit Abschlusspräsentationen
Qualitätsbeauftragte:r mit TÜV Rheinland geprüfter Qualifikation -
Teaching Times: Full-timeMonday to Friday from 8:30 a.m. to 3:35 p.m. (in weeks with public holidays from 8:30 a.m. to 5:10 p.m.)
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Language of Instruction: German
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Duration: 8 Weeks
Quality officers with TÜV Rheinland-certified qualifications
Fundamentals of Quality Management (approx. 1 day)
Terms and Definitions
Quality Management
Quality Management Systems
Standards and Guidelines
Structure of the Standard According to the Harmonized Structure
Fundamentals of Litigation (approx. 1 day)
What Is a Process?
Process Management According to ISO 9001
Identification of Processes
ISO 9001 Process Model
AI-Supported Process Analysis and Optimization
Organizational Context (approx. 1 day)
Organizational Context
Organizational Context with Climate Change Aspects
Stakeholders
Scope of Application
Management (approx. 1.5 days)
Commitment to the QM system
Quality policy
Responsibilities and powers
Planning (approx. 1 day)
Managing Risks, Opportunities, and Actions
Quality Objectives and Planning
Planning for Changes
Opportunities and Risks in the Use of AI in Quality Management
Support (approx. 2.5 days)
Resources
Competence
Awareness
A culture of quality and ethical behavior as an integral part of awareness
Communication
Organizational Knowledge, Knowledge Management
Use of AI applications to support competency development and knowledge management
Documentation of the Quality Management System
Requirements for documented information as evidence of effectiveness and implementation
Operations (approx. 2 days)
Operational Planning
Requirements for Products and Services
Development
Proactive defect prevention using FMEA, QFD, and Poka Yoke
AI-supported methods for predictive defect detection (Predictive Quality)
External Provision
Supply Chain Act (LkSG) and EU Sustainability Directive (CSDDD)
Production and Service Delivery
Approval of products and services
Management of Non-Conforming Results
Performance Evaluation (approx. 1.5 days)
Monitoring and Measurement
AI-powered data analysis and evaluation
Internal audit
Management review
Improvement (approx. 1 day)
Non-conformity and corrective actions
Continuous improvement
Auditing and Certification (approx. 1 day)
Fundamentals of Auditing
Internal Audits
Audit Process
Auditing External Providers or Third Parties
Certification Audit
Communication (approx. 1.5 days)
Building Blocks of Communication
The Iceberg Principle of Communication
The Four-Ears Model
Communication Behavior in Audits
Project management (approx. 1 day)
Definition of project
Managing projects successfully
Total Quality Management (approx. 1 day)
Quality in an Organization
ISO 9004: Guidance on Achieving Sustainable Success
EFQM Model for Excellence
Project work, certification preparation and certification examination "Quality Officer with TÜV Rheinland certified qualification" (approx. 3 days)
Statistics and data analysis
Statistical basics (approx. 6 days)
Measurement theory basics (population, sample, sample types, measurement, scale levels)
Univariate descriptive statistics (frequency distributions, central measures, measures of dispersion, standardization, histograms, bar charts, pie charts, line charts, box plots)
Bivariate descriptive statistics (measures of correlation, correlation coefficients, crosstabs, scatter plots, grouped bar charts)
Basics of inductive inferential statistics (probability distributions, normal distribution, sampling distribution of the mean, significance test, null hypothesis test, significance level, effect size, parameter estimation, confidence intervals, error bar charts, power analysis, sample size)
Data preparation and data cleansing with suitable software
Descriptive analysis
Visualization of statistical results
AI-supported analysis and interpretation of statistical results
Methods for comparing two groups (approx. 5 days)
z-test, t-test for one sample
t-test for independent and related samples
Pretest-posttest designs with two groups
Supporting significance tests (Anderson-Darling test, Ryan-Joiner test, Levene test, Bonett test, significance test for correlations)
Nonparametric methods (Wilcoxon test, sign test, Mann-Whitney test)
Contingency analyses (binomial test, Fisher's exact test, chi-square test, cross-tabulations, measures of association)
Interpretation of test results
AI-supported interpretation of results
Basics of regression analysis (approx. 2 days)
Linear regression
Model interpretation
AI-supported model interpretation
Correlation analysis
Methods for comparing the means of several groups (approx. 3 days)
One-factorial and two-factorial analysis of variance (ANOVA)
Post-hoc analyses
Interpretation of group differences
Multi-factorial analysis of variance (general linear model)
Fixed, random, crossed and nested factors
Multiple comparison methods (Tukey-HSD, Dunnett, Games-Howell)
Interaction analysis
Power analysis for variance analyses
Introduction to Design of Experiments (DoE) (approx. 1 day)
Full factorial and partial factorial experimental designs
Project work (approx. 3 days)
To consolidate the content learned
Presentation of the project results
Changes are possible, the course content is updated regularly.
Once you have completed the course, you will be able to plan, implement, and maintain a quality management system and monitor its effectiveness. You’ll also gain professional expertise in applying the DIN EN ISO 9001 standard, planning internal quality audits, and making effective use of AI-powered tools in quality management.
You will also understand the basics of statistics, be able to process and evaluate data and present, explain and interpret statistical data analyses and results using graphics.
The course is aimed at managers and employees who are entrusted with quality management, who are to implement a QM system in practice or who would like to develop in the area of quality management, as well as specialists and managers from production and service companies who are actively involved in the QM system and quality improvement.
Specialists in the field of quality management are in demand from both large and medium-sized companies in industry, trade and the service sector.
After the course, you will be able to demonstrate your new skills with a TÜV Rheinland-certified qualification.
Didactic concept
Your lecturers are highly qualified both professionally and didactically and will teach you from the first to the last day (no self-study system).
You will learn in effective small groups. The courses usually consist of 6 to 25 participants. The general lessons are supplemented by numerous practical exercises in all course modules. The practice phase is an important part of the course, as it is during this time that you process what you have just learned and gain confidence and routine in its application. The final section of the course involves a project, a case study or a final exam.
Virtual classroom alfaview®
Lessons take place using modern alfaview® video technology - either from the comfort of your own home or at our premises at Bildungszentrum. The entire course can see each other face-to-face via alfaview®, communicate with each other in lip-sync voice quality and work on joint projects. Of course, you can also see and talk to your connected trainers live at any time and you will be taught by your lecturers in real time for the entire duration of the course. The lessons are not e-learning, but real live face-to-face lessons via video technology.
The courses at alfatraining are funded by Agentur für Arbeit and are certified in accordance with the AZAV approval regulation. When submitting a Bildungsgutscheinor Aktivierungs- und Vermittlungsgutschein, the entire course costs are usually covered by your funding body.
Funding is also possible via Europäischen Sozialfonds (ESF), Deutsche Rentenversicherung (DRV) or regional funding programs. As a regular soldier, you have the option of attending further training courses via Berufsförderungsdienst (BFD). Companies can also have their employees qualified via funding from Agentur für Arbeit (Qualifizierungschancengesetz).